{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:BNCST4KA2327MEPK5Y47ELDSQ4","short_pith_number":"pith:BNCST4KA","canonical_record":{"source":{"id":"1905.11901","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2019-05-28T15:59:21Z","cross_cats_sorted":[],"title_canon_sha256":"44e2d1f3d31716e9035017c98a052808ed97d9a1c65aba708fd16d839df03694","abstract_canon_sha256":"ea26b526b3537a8f5f27976492ae29a27d06a5317566aac3beb446a3e1abcbbb"},"schema_version":"1.0"},"canonical_sha256":"0b4529f140d6f5f611eaee39f22c7287309355461e8b7b4394c80491cbbd7269","source":{"kind":"arxiv","id":"1905.11901","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.11901","created_at":"2026-05-17T23:44:49Z"},{"alias_kind":"arxiv_version","alias_value":"1905.11901v1","created_at":"2026-05-17T23:44:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.11901","created_at":"2026-05-17T23:44:49Z"},{"alias_kind":"pith_short_12","alias_value":"BNCST4KA2327","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"BNCST4KA2327MEPK","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"BNCST4KA","created_at":"2026-05-18T12:33:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:BNCST4KA2327MEPK5Y47ELDSQ4","target":"record","payload":{"canonical_record":{"source":{"id":"1905.11901","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2019-05-28T15:59:21Z","cross_cats_sorted":[],"title_canon_sha256":"44e2d1f3d31716e9035017c98a052808ed97d9a1c65aba708fd16d839df03694","abstract_canon_sha256":"ea26b526b3537a8f5f27976492ae29a27d06a5317566aac3beb446a3e1abcbbb"},"schema_version":"1.0"},"canonical_sha256":"0b4529f140d6f5f611eaee39f22c7287309355461e8b7b4394c80491cbbd7269","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:44:49.974351Z","signature_b64":"GmqrSZ1sP8yCLPjNme7O5yI9+87RfbzHuwu4lkqrjHFnJ15UtQrDgAntpN3YRUmHd8qzfsse/gHJCkpnRH3ODg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0b4529f140d6f5f611eaee39f22c7287309355461e8b7b4394c80491cbbd7269","last_reissued_at":"2026-05-17T23:44:49.973809Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:44:49.973809Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1905.11901","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:44:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vpqDd8X0okcQYaanIYaZ2rRhHC3s0J58CJuZxlZtxD59aa+UQ5lAKjsO8eOntxNer9kkj+BNgbXv18Z/9Yy9Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T21:47:18.081107Z"},"content_sha256":"0324512f7393bd169358ce6ea4c04e65a589370ce8cd05c764e342f039c65f43","schema_version":"1.0","event_id":"sha256:0324512f7393bd169358ce6ea4c04e65a589370ce8cd05c764e342f039c65f43"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:BNCST4KA2327MEPK5Y47ELDSQ4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Revisiting Low-Resource Neural Machine Translation: A Case Study","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Biao Zhang, Rico Sennrich","submitted_at":"2019-05-28T15:59:21Z","abstract_excerpt":"It has been shown that the performance of neural machine translation (NMT) drops starkly in low-resource conditions, underperforming phrase-based statistical machine translation (PBSMT) and requiring large amounts of auxiliary data to achieve competitive results. In this paper, we re-assess the validity of these results, arguing that they are the result of lack of system adaptation to low-resource settings. We discuss some pitfalls to be aware of when training low-resource NMT systems, and recent techniques that have shown to be especially helpful in low-resource settings, resulting in a set o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.11901","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:44:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tZ8peq5dsOdFfDvASXlGXNuQlcGRXMQ3szN+A8fCEO9K5p1yKuYoIvlxS+xUt5Fu/c+36DIUNA3eXnEwD5vpAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T21:47:18.081474Z"},"content_sha256":"aab9b03ac364c635e660e75da70a14e7add92305a8a91d203ac724929ea39c24","schema_version":"1.0","event_id":"sha256:aab9b03ac364c635e660e75da70a14e7add92305a8a91d203ac724929ea39c24"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BNCST4KA2327MEPK5Y47ELDSQ4/bundle.json","state_url":"https://pith.science/pith/BNCST4KA2327MEPK5Y47ELDSQ4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BNCST4KA2327MEPK5Y47ELDSQ4/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-03T21:47:18Z","links":{"resolver":"https://pith.science/pith/BNCST4KA2327MEPK5Y47ELDSQ4","bundle":"https://pith.science/pith/BNCST4KA2327MEPK5Y47ELDSQ4/bundle.json","state":"https://pith.science/pith/BNCST4KA2327MEPK5Y47ELDSQ4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BNCST4KA2327MEPK5Y47ELDSQ4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:BNCST4KA2327MEPK5Y47ELDSQ4","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"ea26b526b3537a8f5f27976492ae29a27d06a5317566aac3beb446a3e1abcbbb","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2019-05-28T15:59:21Z","title_canon_sha256":"44e2d1f3d31716e9035017c98a052808ed97d9a1c65aba708fd16d839df03694"},"schema_version":"1.0","source":{"id":"1905.11901","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.11901","created_at":"2026-05-17T23:44:49Z"},{"alias_kind":"arxiv_version","alias_value":"1905.11901v1","created_at":"2026-05-17T23:44:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.11901","created_at":"2026-05-17T23:44:49Z"},{"alias_kind":"pith_short_12","alias_value":"BNCST4KA2327","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"BNCST4KA2327MEPK","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"BNCST4KA","created_at":"2026-05-18T12:33:12Z"}],"graph_snapshots":[{"event_id":"sha256:aab9b03ac364c635e660e75da70a14e7add92305a8a91d203ac724929ea39c24","target":"graph","created_at":"2026-05-17T23:44:49Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"It has been shown that the performance of neural machine translation (NMT) drops starkly in low-resource conditions, underperforming phrase-based statistical machine translation (PBSMT) and requiring large amounts of auxiliary data to achieve competitive results. In this paper, we re-assess the validity of these results, arguing that they are the result of lack of system adaptation to low-resource settings. We discuss some pitfalls to be aware of when training low-resource NMT systems, and recent techniques that have shown to be especially helpful in low-resource settings, resulting in a set o","authors_text":"Biao Zhang, Rico Sennrich","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2019-05-28T15:59:21Z","title":"Revisiting Low-Resource Neural Machine Translation: A Case Study"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.11901","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:0324512f7393bd169358ce6ea4c04e65a589370ce8cd05c764e342f039c65f43","target":"record","created_at":"2026-05-17T23:44:49Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"ea26b526b3537a8f5f27976492ae29a27d06a5317566aac3beb446a3e1abcbbb","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2019-05-28T15:59:21Z","title_canon_sha256":"44e2d1f3d31716e9035017c98a052808ed97d9a1c65aba708fd16d839df03694"},"schema_version":"1.0","source":{"id":"1905.11901","kind":"arxiv","version":1}},"canonical_sha256":"0b4529f140d6f5f611eaee39f22c7287309355461e8b7b4394c80491cbbd7269","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0b4529f140d6f5f611eaee39f22c7287309355461e8b7b4394c80491cbbd7269","first_computed_at":"2026-05-17T23:44:49.973809Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:44:49.973809Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GmqrSZ1sP8yCLPjNme7O5yI9+87RfbzHuwu4lkqrjHFnJ15UtQrDgAntpN3YRUmHd8qzfsse/gHJCkpnRH3ODg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:44:49.974351Z","signed_message":"canonical_sha256_bytes"},"source_id":"1905.11901","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0324512f7393bd169358ce6ea4c04e65a589370ce8cd05c764e342f039c65f43","sha256:aab9b03ac364c635e660e75da70a14e7add92305a8a91d203ac724929ea39c24"],"state_sha256":"5c25d8ab507d21f467bec4e3ad1129f1ecdd63c5d8ebb00390ff7076e0c20259"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8HIcyT0ynjDTAflrtxn7wwiR+nvrMmeRME1i0FpH3O+JKUoQYqHPW8yRwcf/7UxhEdzAgI2SSSvk6kHV+KeMDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T21:47:18.083379Z","bundle_sha256":"080291cd6892ad75a1cf835a2838e9d644e6f1e901daeabd89c3e5e6317c13b6"}}